Making AI Workflows Predictable with MCP and Bifrost

LLM development quickly expanded beyond simple experiments. Today, AI systems are not just text generation, but full-fledged production applications that work with APIs, databases, files, and internal services. MCP (Model Context Protocol) has become a standard that unifies the interaction of models with tools and infrastructure. But with increasing complexity, a new problem arises is manageability. The more MCP servers, tools, and integrations there are, the less predictable the behavior of the model becomes: the choice of tools, sequence of actions, cost, and stability of results. This is where the production-grade LLM gateway is needed. The combination of Bifrost MCP Gateway and Code Mode transforms MCP from an experimental integration layer into a managed, scalable and predictable infrastructure , where orchestration is transferred from promptness to code, and LLM begins to do what it does best, reasoning and decision-making, rather than "juggling" tools. 💻 From MCP to production v